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| Main Author: | |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.06210 |
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| _version_ | 1866908694602579968 |
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| author | Komarov, Pavel |
| author_facet | Komarov, Pavel |
| contents | One of the happiest accidents in all math is the ease of transforming a function to and taking derivatives in the Fourier frequency domain. But in order to exploit this extraordinary fact without serious artefacting, and in order to be able to use a computer, we need quite a bit of extra knowledge and care. This document sets out the math behind the spectral-derivatives Python package. I touch on fundamental signal processing and calculus concepts as necessary and build upwards. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_06210 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Spectral Derivatives Komarov, Pavel Signal Processing History and Overview One of the happiest accidents in all math is the ease of transforming a function to and taking derivatives in the Fourier frequency domain. But in order to exploit this extraordinary fact without serious artefacting, and in order to be able to use a computer, we need quite a bit of extra knowledge and care. This document sets out the math behind the spectral-derivatives Python package. I touch on fundamental signal processing and calculus concepts as necessary and build upwards. |
| title | Spectral Derivatives |
| topic | Signal Processing History and Overview |
| url | https://arxiv.org/abs/2506.06210 |